ArticlePharmaceutics2023
Characterization and Validation of a New 3D Printing Ink for Reducing Therapeutic Gap in Pediatrics through Individualized Medicines.
Article in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Reusable gelatin-based inks for 3D printing of veterinary gabapentin tablets: a sustainable approach.Frontiers in veterinary science · 2026Article
- Development of 3D-Printed Hydrogel Disks as Standardized Platform for Evaluating Excipient Impact on Metronidazole's Antimicrobial Activity.Pharmaceutics · 2025Article
- Three-Dimensional-Printed Isoniazid Chewable Gels for On-Demand Latent Tuberculosis Treatment in Children.Pharmaceutics · 2025Article
- The Design of Novel 3D-Printed, Moulded, and Oral Viscous Budesonide Formulations for Paediatrics: A Comparative Evaluation of Their Mucoadhesive Properties.Pharmaceutics · 2024Article
- Revolutionizing Three-Dimensional Printing: Enhancing Quality Assurance and Point-of-Care Integration through Instrumentation.Pharmaceutics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
3D printing technology can be used to develop individualized medicines in hospitals and pharmacies, allowing a high degree of personalization and the possibility to adjust the dose of the API based on the quantity of material extruded. The main goal of incorporating this technology is to have a stock of API-load print cartridges that could be used at different storage times and for different patients. However, it is necessary to study the extrudability, stability, and buildability of these print cartridges during storage time. A paste-like formulation containing hydrochlorothiazide as a model drug was prepared and distributed in five print cartridges, each of which was studied for different storage times (0 h-72 h) and conditions, for repeated use on different days. For each print cartridge, an extrudability analysis was performed, and subsequently, 100 unit forms of 10 mg hydrochlorothiazide were printed. Finally, various dosage units containing different doses were printed, taking into account the optimized printing parameters based on the results of the extrudability analysis carried out previously. An appropriate methodology for the rapid development of appropriate SSE 3DP inks for pediatrics was established and evaluated. The extrudability analysis and several parameters allowed the detection of changes in the mechanical behavior of the printing inks, the pressure interval of the steady flow, and the selection of the volume of ink to be extruded to obtain each of the required doses. The print cartridges were stable for up to 72 h after processing, and orodispersible printlets containing 6 mg to 24 mg of hydrochlorothiazide can be produced using the same print cartridge and during the same printing process with guaranteed content and chemical stability. The proposed workflow for the development of new printing inks containing APIs will allow the optimization of feedstock material and human resources in pharmacy or hospital pharmacy services, thus speeding up their development and reducing costs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.